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Record W2059124518 · doi:10.1037/a0014122

Scalar timing varies with response magnitude in classical conditioning of the nictitating membrane response of the rabbit (Oryctolagus cuniculus).

2009· article· en· W2059124518 on OpenAlexaff
E. James Kehoe, Kirk N. Olsen, Elliot A. Ludvig, Richard S. Sutton

Bibliographic record

VenueBehavioral Neuroscience · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInterstimulus intervalNictitating membraneConditioningClassical conditioningEyeblink conditioningStandard deviationLatency (audio)PsychologyMathematicsStatisticsNeuroscienceAudiologyMedicineComputer science

Abstract

fetched live from OpenAlex

The present experiment was aimed at characterizing the timing of conditioned nictitating membrane (NM) movements as function of the interstimulus interval (ISI) in delay conditioning for rabbits (Oryctolagus cuniculus). Onset latency and peak latency were approximately, but not strictly, scalar for all but the smallest movements (<.10 mm). That is, both the mean and standard deviation of the timing measures increased in proportion to the ISI, but their coefficients of variation (standard deviation/mean) tended to be larger for shorter ISIs. For all ISIs, the absolute timing of the NM movements covaried with magnitude. The smaller movements (approximately, .11-.50 mm) were highly variable, and their peaks tended to occur well after the time of US delivery. The larger movements (>.50 mm) were less variable, and their peaks were better aligned with the time of US delivery. These results are discussed with respect to their implications for current models of timing in eyeblink conditioning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.303
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2009
Admission routes1
Has abstractyes

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